Detaljerad miljöinformation

Environmental Risk Classification

Predicted Environmental Concentration (PEC)

PEC is calculated according to the following formula: (Ref.1)

PEC (μg/L) = (A*10⁹*(100-R))/(365*P*V*D*100)

Where:

A (kg/yr)	17,2127 kg	Total venetoklax (ABT-199) sold (kg) in Sweden in 2021 from IQVIA (Ref. 2)
R	0 %	Removal rate (due to loss by adsorption to sludge particles, by volatilization, hydrolysis or biodegradation); use 0 if no data is available. (Ref.1)
P	10*106	Number of inhabitants in Sweden (Ref. 1)
V (L/day)	200	Volume of wastewater per capita and day (200 L/day is the default value) (Ref. 1,3)
D	10	Factor for dilution of wastewater by surface water flow (10 is the default value) (Ref. 1,3).

Note: The factor 10⁹ converts the quantity distressed from kg to mcg.

PEC (μg/L) = (17,2127*10⁹*(100-0))/(365*10*10⁶*200*10*100)

PEC = 0,0024 μg/L

Ecotoxicological Studies with venetoklax

Activated Sludge, Respiration Inhibition Test (OECD 209)

An activated sludge respiration inhibition study was conducted in accordance with

OECD 209 at 10, 100, and 1000 (triplicate) mg/L venetoklax. (Ref. 4)

No significant inhibition was observed at any test concentration.

EC₅₀ > 1000 mg/L

EC₁₀ (equivalent to a NOEC) >1000 mg/L

Freshwater Alga Growth Inhibition Test (OECD 201)

An alga growth inhibition study was conducted using Pseudokirchneriella subcapitata in accordance with OECD 201 with the following results. (Ref. 5)

	Endpoint (mg/L)a
	72-Hour Yield	72-Hour Average Specific Growth Rate	72 Hour Area Under the Growth Curve (AUGC)
NOEC	4,8	4,8	4,8

^a. Based on Time-Weighted Average Concentrations

Daphnia magna Reproduction Test (OECD 211)

A 21-day exposure reproduction study was conducted on Daphnia magna in accordance with OECD 211. (Ref. 6)

	Endpoint (mg/L)
	Survival	Reproduction	Length
NOEC	0,0073	0,012	0,012

The most sensitive NOEC was determined to be 0,0073 mg/L (Daphnia survival).

Fish Early-Life Stage Toxicity Test (OECD 210)

A fish early-life stage toxicity study was conducted on fathead minnow (Pimephales promelas) in accordance with OECD 210. (Ref. 7) The objective of this study was to determine the NOEC of fathead minnow embryos and larvae exposed to venetoklax under flow-through conditions for 32-days (28 days post-hatch).

	Endpoint (mg/L) a
	Wet Weight
NOEC	0,013

^a.Based on time-weighted average measured concentrations

Predicted No Effect Concentration (PNEC)

PNEC (mg/L) = NOEC/AF

AF = Assessment Factor= 10

Organism	NOEC
Microorganisms (spps)	>1000 mg/L
Freshwater Algae (Pseudokirchneriella subcapitata)	4,8 mg/L
Daphnia magna	0,0073 mg/L
Fathead Minnow (Lepomis macrochirus)	0,013 mg/L

The PNEC was determined in accordance with ECHA guidance (Ref. 8).

The chronic aquatic effects of venetoklax were assessed in green algae, fish, and Daphnia. Daphnia magna was determined to be the most sensitive species tested (NOEC of 0,0073 mg/L). Therefore, the PNEC_SURFACEWATER was calculated using the NOEC for Daphnia magna.

NOEC = 0,0073 mg/L

PNEC (mg/L) = 0,0073/10

PNEC = 0,00073 mg/L

PNEC = 0,73 μg/L

Environmental Risk Classification (PEC/PNEC ratio)

PEC/PNEC Ratio:

PEC = 0,0024 μg/L

PNEC = 0,73 μg/L

PEC/PNEC = 0,0024/0,73

PEC/PNEC = 0,0033

Justification of environmental risk classification:

Since PEC/PNEC ≤ 0,1, the use of venetoklax has been considered to result in insignificant environmental risk.

Degradation

Aerobic Transformation in Aquatic Sediment Systems (OECD 308)

Aerobic transformation [(evaluated using applied radioactivity (AR)] was examined in an

aquatic sediment study in accordance with OECD 308. (Ref. 9)

The degradation and distribution of [¹⁴C]ABT-199 was investigated according to OECD Guideline 308. The transformation of [¹⁴C]ABT-199 was studied in two different water/sediment systems (Taunton River and Weweantic River Sediments) under aerobic conditions. 

The rate of aerobic transformation of parent [¹⁴C]ABT-199 was studied at a concentration of approximately 0,5 mg/L and a temperature of 20 ± 2 °C for 100 days in two aerobic sediments (with associated overlying waters) varying in pH, textural characteristics, organic matter content and microbial content . Water/sediment samples from each system were analyzed at 0, 3, 14, 27, 56 and 100 days after dosing. The untreated flooded sediment samples were equilibrated under aerobic conditions for seven days. Following equilibration, the water layers of each of the systems were

treated with [¹⁴C]ABT-199 to achieve a final nominal concentration of 0,5 mg/L in the water layer. The aerobic incubation of treated test systems was performed by continuously bubbling hydrated air through the water layer for 100 days. Potassium hydroxide (KOH) and ethylene glycol traps were used in flow through aerobic test systems to collect ¹⁴CO₂ and any volatile components that evolved during the

study.

At each sampling interval, the samples from each test system were separated into water and sediment fractions. Approximately 150 mL of acetonitrile was added to the water fraction. With the exception of Day 0, sediment samples were extracted twice with acetonitrile:purified reagent water (90:10, v:v) and once with acetonitrile:0.1M ammonium carbonate (80:20, v:v) for a total of three extractions. The Day 0 sediment samples were extracted once using acetonitrile:purified reagent water. In addition, the

Day 0 Taunton River sediment samples were extracted a second time using acetonitrile:purified reagent water. The water phase and sediment extracts were radioassayed by liquid scintillation counting (LSC) and also analyzed by high performance liquid chromatography equipped with radiochemical detection (HPLC/RAM) to quantify [¹⁴C]ABT-199 and degradation products in the fractions. The water phase was analyzed by HPLC/RAM through Day 27. The radioactivity in the post extracted solids (sediment-bound) was quantified by combustion analysis. The volatile organic traps were radio-assayed by LSC.

Average material balance ranged from 85,4 to 100,5% of the applied radioactivity (% AR) over the course of the 100-day study. Ultimate biodegradation was observed in the aerobic test systems.

The half-lives for water, sediment, and total system were determined to be as follows:

	Layer	Taunton River	Weweantic River
DT50, 20°C (days)	Water	7,8	11
	Sediment	173	57
	Total System	87	47

As is shown, the DT₅₀ values for the total system in the Taunton River and the Weweantic River systems were 87 and 47 days, respectively. In addition, ultimate biodegradation was observed in both aerobic test systems (with evolution of

¹⁴CO₂ reaching an average maximum at Day 100 of 1,90% AR in the Taunton River system and 3,50% AR in the Weweantic River system).

Justification of chosen degradation phrase:

DT₅₀< 120d for the total system; therefore, venetoklax is slowly degraded in the environment.

Bioaccumulation

Partition Coefficient (OECD 123)

The n-octanol/water partition coefficient of venetoklax was determined using the slow‑stirring method in accordance with OECD 123. (Ref. 10)

pH	Log Pow
4	5,79
7	5,91
9	4,77

Bioaccumulation Analysis: Dietary Exposure Bioaccumulation Fish Test (OECD 305-III)

As the Log P_ow at pH 7 was greater than 3, a dietary exposure bioaccumulation study was conducted in accordance with OECD 305-III. The results of the study using bluegill sunfish (Lepomis macrochirus) exposed to [¹⁴C]venetoklax were as follows. (Ref. 11)

Parameter	Result
Nominal mg [14C]venetoklax/kg	100
Half-life (day)	0,39
Growth corrected half-life (day)	0,39
Biomagnification factor (BMF, (I x α)/k2)	0,008
Growth-corrected biomagnification factor(BMFg, (I x α)/k2g)	0,008
Lipid-corrected biomagnification factor (BMFL, BMF/Lc)	0,0047
Growth and lipid-corrected biomagnification factor (BMFLg, BMFg/Lc)	0,0048

The BMF values were all substantially < 0,1 and the depuration half-life was 0,39 days, indicating that venetoklax will not bioaccumulate in fish.

The BMF values were used to calculate the BCF values using Methods 1, 2, and 3 (Ref. 12, 13, 14, 15).

Calculated BCF Values
Method 1a	Method 2b	Method 3c
224	121	159
313
307
197
320
61
244
200
233
418
354
52
89

a.         Method 1 BCF was estimated using rate constant (K1).

b.         Method 2 BCF was estimated using depuration rate (K2gl).

c.         Method 3 BCF was estimated using BMF factor (BMFgl).

The calculated BMC values were all < 500, thereby substantiating that venetoklax will not bioaccumulate in fish (Ref. 12).

Justification of chosen bioaccumulation phrase:

Venetoklax has low potential for bioaccumulation.

References

1. FASS.se. Environmental classification of pharmaceuticals at www.fass.se. Guidance for pharmaceutical companies. 2012 V 2.0. 2021.

2. IQVIA. 2022. IQVIA / LIF - kg consumption/2021.

3. European Chemicals Agency (ECHA). Guidance on Information Requirements and Chemical Safety Assessment Chapter R.16: Environmental exposure assessment. Version 3.0. 2016.

4. Smithers Viscient. AbbVie Report R&D/14/0594. ABT-199 - Activated Sludge Respiration Inhibition Test Following OECD Guideline 209. 26 Feb 2015.

5. Smithers Viscient. AbbVie Report R&D/14/0595. ABT-199 - 72-Hour Toxicity Test with the Freshwater Green Alga, Pseudokirchneriella subcapitata Following OECD Guideline 201. 26 Feb 2015.

6. Smithers Viscient. AbbVie Report R&D/14/0596. ABT-199 - Full Life-Cycle Toxicity Test with Water Fleas, Daphnia magna, Under Flow-Through Conditions Following OECD Guideline 211. 09 Jul 2015.

7. Smithers Viscient. AbbVie Report R&D/14/0597. ABT-199 - Early Life-Stage Toxicity Test with Fathead Minnow (Pimephales promelas). Amended 5 Jan 2016.

8. European Chemicals Agency (ECHA). Guidance on information requirements and chemical safety assessment Chapter R.10: Characterisation of dose [concentration]-response for environment. 2008.

9. Smithers Viscient. AbbVie Report R&D/14/0593. [14C]ABT-199 - Aerobic Transformation in Aquatic Sediment Systems Following OECD Guideline 308. 08 Jun 2015.

10. Smithers Viscient. AbbVie Report R&D/15/0288. ABT-199 - Determining the Partitioning Coefficient (n-Octanol/Water) at Three pH by the Slow-Stirring Method Following OECD Guideline 123. Amended 11 Jan 2016.

11. Smithers Viscient. AbbVie Report R&D/15/0279. [14C]ABT-199 – Dietary Bioaccumulation Study with Bluegill Sunfish (Lepomis macrochirus) Under Flow-Through Conditions. 28 Aug 2015.

12. AbbVie.  R&D/22/1491. Conversion of Venetoklax BMF to BCF.  30 June 2022.

13. Organisation for Economic Co-operation and Development (OECD). Draft Guidance Document on Aspects of OECD Test Guideline 305 on Fish Bioaccumulation. 29th Meeting of the Working Group of the National Coordinators of the Test Guidelines Programme, 25-28th April 2017, OECD Headquarters, 2 rue André-Pascal 75775 Paris cédex 16. ENV/JM/TG(2017)10. 06-Mar-2017.  Accessed 9 June 2022.  Available URL: https://one.oecd.org/document/ENV/JM/TG(2017)10/en/pdf

14. Organisation for Economic Co-operation and Development (OECD). OECD Test No. 305: Bioaccumulation in Fish: Aqueous and Dietary Exposure, OECD Guidelines for the Testing of Chemicals, Section 3, OECD Publishing, Paris.  2 October 2012.  https://doi.org/10.1787/9789264185296-en.

15. European Chemicals Agency (ECHA).  Guidance on Information Requirements and Chemical Safety Assessment Chapter R.7c: Endpoint specific guidance Version 3.0.  June 2017.

Appendix - Conversion of Venetoklax BMF to BCF

Bioaccumulation Results of Bluegill Sunfish Exposed to [¹⁴C]Venetoklax ([¹⁴C)ABT-199)

Notes on the Conversion of from Venetoclax BCF to BMF

• BCF estimates are calculated for the 3 methods presented in the Guidance Document; how to compare the relevance of these estimates is described in the OECD 305 Bioaccumulation in Fish, Annex 8.

• All estimates are based on a fish of 5% lipid content (for methods 1 and 2 the depuration rate constant is normalised to 5% lipid; for method 3 normalisation to 5% lipid is implicit as the equation was derived using BCF data normalised to 5%).

• Normalisation of the depuration rate constant is from the estimated mean lipid content at the midpoint of the depuration phase, based on mean lipid content at the end of uptake/start of depuration and mean content at the end of the depuration phase assuming a linear relationship with time; if additional lipid contents measured during the depuration phase, then mean lipid content midpoint depuration phase value can be replaced with a separate value derived using all datapoints.

• Method 1 consists of a number of models to estimate K1. Most models use fish weight, estimated for the midpoint of the uptake phase, which is estimated using the mean fish starting weight, growth rate (calculated for the entire study according to OECD 305) and duration of the uptake phase.

• For methods 2 and 3, which do not include a step in which a K1 value is calculated, K1 estimates are presented here for comparative purposes based on the estimated BCF multiplied by the K2gl value.

Summary of Indicative Applicability Domains for the Three BCF Estimation Methods

Inputs
Variable	Value
Mean weight at test start (g)	3,07476
Uptake phase duration (days)	14
Growth rate, Kg (day-1)	0,0194
Log KOW	5,6
K2 g (K2 - Kg)	1,76
Mean fish lipid uptake end or depuration start (fraction)	0,0411
Mean fish lipid depuration end (fraction)	0,0608
Depuration phase duration (days)	28
BMFg l	0,0048
Interim Outputs
Variable	Value
Mean weight midpoint uptake phase (g)	3,193
Mean lipid content midpoint depuration phase	0,051
K2 g l	1,793

BCF Estimates Obtained from Methods 1, 2, and 3

Outputsa
Method 1b
Inputs for K1	K1	BCF Estimate	Reference
weight	401,20	223,7	Hayton and Barron (1990)
weight	560,44	312,5	Erickson and McKim (1990a)
weight	550,98	307,2	Barber et al. (1991)
weight	354,02	197,4	Barber (2003) - observed
weight	574,83	320,5	Barber (2001)
weight	108,68	60,6	Streit and Sire (1993)
weight	437,16	243,8	Erickson and McKim (1990b)
weight	358,64	200,0	Sijm et al. (1995)
weight	417,92	233,0	Barber (2003) - calibrated
log Kow	750,24	418,3	Tolls and Sijm (1995)
log Kow	635,62	354,4	Spacie and Hamelink (1982)
weight, log Kow	93,85	52,3	Hendriks et al. (2001)
weight, log Kow	160,00	89,2	Thomann (1989)
Method 2c
Input	Estimated K1	BCF Estimate	Reference
K2 g l	217,36	121,2	Brookes and Crooke (2012)
Method 3d
Input	Estimated K1	BCF Estimate	Reference
BMFg l	284,29	158,5	Inoue et al (2012)

1. Above all data are from the BMF study report except LogKow.

2. Based on the above data, in Method 1 BCF was estimated using rate constant (K1).

3. Based on the above data, in Method 2 BCF was estimated using depuration rate (K2gl).

4. Based on the above data, in Method 3 BCF was estimated using BMF factor (BMFgl).

BCF Estimations from Dietary Study Data: Strengths and Weaknesses on the Conversion of Venetoklax BMF to BCF

Adapted from Guidance on Information Requirements and Chemical Safety Assessment Chapter R.7c: Endpoint specific guidance Version 3.0. June 2017.

1. Calculated BCFs may be more uncertain than experimental BCFs due to the uncertainty in the k1 prediction. Assuming k1 is accurately and appropriately predicted for the substance and the conditions of the experiment, the tentative BCF values from a dietary test could be determined. However, as there are always other metrics also available from a dietary test, the calculated BCFs should be considered as part of the body of evidence, and not used as the only values from which to draw conclusions in the PBT assessment.

2. For poorly soluble non-polar organic substances, which includes Venetoklax, first order uptake and depuration kinetics is assumed, and more complex kinetic models should be used only for substances that do not follow first order kinetics. Several models are available to estimate a k1 value needed to calculate an aqueous BCF from a dietary bioaccumulation study.  As can be seen in the tables above, a number of k1 values were used to estimate BCF.

3. The OECD TG 305 III: Dietary Exposure Bioaccumulation Fish Test provides a range of valuable information which should all be discussed in the bioaccumulation assessment.

Adapted from Draft Guidance Document on Aspects of OECD Test Guideline 305 on Fish Bioaccumulation, ENV/JM/TG(2017)10. 6-Mar-2017.

The below are three approaches used to estimate a BCF from the BMF data for Venetoklax.

• Method 1: Uptake rate constant estimation method

• Method 2: Relating depuration rate constant directly to BCF.

• Method 3: Correlating dietary BMF with BCF

The “pros” and “cons” of each of these methods, as presented in the Draft Guidance Document on OECD 305 on Fish Bioaccumulation (06 March 2017) are presented below.

A. Method 1: Uptake rate constant estimation method

Some of the issues for this method are discussed in Annex 8 to OECD 305. The paragraphs below summarise these and other issues relevant for the uptake rate constant estimation method.

Pros of the uptake rate constant estimation method include:

• A general approach that can be used with readily available input data from a dietary study;

• The large number of available models with differing input parameters, allow flexibility; and

• In many models large and varied underlying datasets covering different ranges and types of substances and sizes and species of fish.

Cons of the uptake rate constant estimation method include:

• The large number of available models give a wide range of results for k1, differing by a factor of two to three for those assessed by Crookes and Brooke (36), with no reliable way of discriminating between estimates based on combinations of substance and model;

• Limited information for some models on training and validation datasets and so limited ways of judging a model’s applicability domain with respect to test substance;

• Respiratory uptake is taken to be a thermodynamic process largely driven by passive diffusion across the gill. Since the models do not take account of test substance-related factors that may affect passive diffusion like molecular weight and size, or ionisability, resulting uptake rate constants may be overestimated unless care is taken with regard to a substance’s structure and properties. In extreme cases, substances that only very poorly absorb across the gut and so have very low dietary BMFs may however have high predicted BCFs based on high estimated uptake rate constants using this method. Hence information on the applicability domain is critical;

• Low correlation when models were tested with data from available BCF study datasets; and

• For high log KOW substances, Gobas and Lo (61) make some assumptions about gill respiration. They assume k1 will be low, and to be identical or approach zero as log KOW approaches infinity. Therefore, this contradicts the current approach of method 1. This requires further consideration.

B. Method 2: Relating depuration rate constant directly to BCF/ Using available BCF data to determine k2 25 values equivalent to regulatory thresholds of 2000 and 5000

Because this second method is closely related to the first method described above, many of the pros and cons overlap.

Pros of relating depuration rate constant directly to BCF include:

• A general and simple approach that can be used with readily available input data from a dietary study;

• Large underlying datasets, covering different ranges and types of substances, and sizes and species of fish; and

• Possibility to derive relationships for specific fish species and sizes that are being tested, assuming BCF studies for these species and fish sizes are available.

Cons of relating depuration rate constant directly to BCF include:

• The large variety of fish species and sizes may not relate well to dietary study species and fish size and may result in low accuracy of predictions;

• Uncertainties in the underlying datasets owing to limited test conduct information; and

• Respiratory uptake is taken to be a thermodynamic process largely driven by passive diffusion across the gill. As was described above for the uptake rate constant estimation method, this method does not take account of test substance-related factors that may affect passive diffusion like molecular weight and size, or ionisability. This may result in overestimated BCF values. In extreme cases, substances that only very poorly absorb across the gut and so have very low dietary BMFs may however have high BCFs predicted because of the underlying basis of this method. Hence, information on the applicability domain is critical.

C. Method 3: Using a correlation of dietary BMF and BCF results to interpolate other BMF results

Pros of correlating dietary BMF with BCF include:

• Estimations following this approach take account of uptake in the dietary study, unlike the two approaches described above where uptake and depuration are “decoupled”. This means that situations where uptake in reality would be very low based on issues with bioavailability and passive diffusion but predicted uptake rate constants and BCFs are overestimated, are likely to be avoided with this approach; and

• This approach could be considered more of a “metrics conversion” than an extrapolation, which is the case with the preceding two methods. If the assumption holds that depuration is the same regardless of uptake route given sufficient time for in vivo distributions to normalise, this method is basically comparing uptake rates between different exposure routes (Mackay et al.’s “equilibrium multiplier”). This could be considered a more “transparent” data transformation

Cons of correlating dietary BMF with BCF include:

• The training set for the regression is very small and generally includes more bioaccumulative chemicals. The latter point may mean that the linear regression may be “skewed”;

• The intercept of the correlation is not x,y = 0. Instead, if BMF = 0, BCF is a positive value. One reason for this is the difference in uptake routes. This is because the comparison is between diffusion across aqueous layer at the gill vs. assimilation efficiency in the gut as well as metabolism in the gastro-intestinal tract vs. at the gill;

• The extents of gut metabolism of the different chemicals in the correlation (training set) are not known, which could affect the slope of the correlation. This is also a consideration when applying the correlation to test substance results; and

• Error associated with correlation (due to the test results themselves) is not known, which may be significant for the correlation given the small number of data points.

References

1. European Chemicals Agency (ECHA). Guidance on Information Requirements and Chemical Safety Assessment Chapter R.7c: Endpoint specific guidance Version 3.0. June 2017.

2. Organisation for Economic Co-operation and Development (OECD). OECD Test No. 305: Bioaccumulation in Fish: Aqueous and Dietary Exposure, OECD Guidelines for the Testing of Chemicals, Section 3, OECD Publishing, Paris.  2 October 2012.

3. Organisation for Economic Co-operation and Development (OECD). Draft Guidance Document on Aspects of OECD Test Guideline 305 on Fish Bioaccumulation. 29th Meeting of the Working Group of the National Coordinators of the Test Guidelines Programme, 25-28th April 2017, OECD Headquarters, 2 rue André-Pascal 75775 Paris cédex 16. ENV/JM/TG(2017)10. 06-Mar-2017.  Accessed 9 June 2022.  Available URL: https://one.oecd.org/document/ENV/JM/TG(2017)10/en/pdf